Prescription Opioid Use, Harms andInterventions in Canada: A Review Update ofNew Developments and Findings since 2010
Notice bibliographique
Résumé
BACKGROUND: Canada has featured the second-highest levels of prescription opioid (PO) use globally behind the United States, and reported extensive PO-related harms (e.g., non-medical PO use [NMPOU], PO-related morbidity and mortality). A recent comprehensive review synthesized key data on PO use, PO-related harms, and interventions in Canada, yet a substantive extent of new studies and data have emerged. OBJECTIVE: To conduct and present a comprehensive review update on PO use, PO-related harms, and interventions in Canada since 2010. STUDY DESIGN: Narrative review METHODS: We conducted literature searches, employing pertinent keywords, in key databases, focusing on PO-related studies/data in/for Canada since 2010, or pertinent studies/data from earlier periods not included in our previous review. In addition, we identified relevant data from "grey" literature (e.g., government, survey, other data or system reports). Relevant data were screened and extracted, and categorized into 4 main sections of indicators: 1) PO dispensing and use, 2) non-medical PO use, 3) PO-related morbidity/mortality, 4) PO-related interventions and impacts. RESULTS: PO-dispensing in Canada overall continued to increase and/or remain at high levels in Canada from 2010 to 2013, with the exception of the province of Ontario where marked declines occurred starting in2012; quantitative and qualitative PO dispensing patterns continued to vary considerably between provinces. Several studies identified common "high PO dosing" prescribing practices in different settings. Various data suggested declining NMPOU levels throughout most general (e.g., adult, students), yet not in special risk (e.g., street drug users, First Nations) populations. While treatment demand in Ontario plateaued, rising PO-related driving risks as well as neo-natal morbidity were identified by different studies. PO-related mortality was measured to increase--in total numbers and proportionally--in various Canadian jurisdictions. Select reductions in general PO and/or high-dose PO dispensing were observed following key interventions (e.g., Oxycodone delisting, prescription monitoring program [PMP] introduction in Ontario/British Columbia). While physician education intervention studied indicated mixed outcomes, media reporting was found to be associated with PO prescribing patterns. LIMITATIONS: The present review did not utilize systematic review standards or meta-analytic techniques given the large heterogeneity of data and outcomes reviewed. CONCLUSIONS: Recently emerging data help to better characterize PO-related use, harm and intervention indicators in Canada's general context of comparatively high-level PO dispensing and harms, yet major gaps in monitoring and information persist; this continues to be a problematic challenge, especially given the implementation of key PO-related interventions post-2010, the impact of which needs to be properly measured and understood.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,011 | 0,034 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,004 |
| Bibliométrie | 0,022 | 0,032 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,006 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».